I think that the “basic physics” of radiative transfer and atmospheric convection is challenging enough, and the question of feedback even harder.

There are hundreds of papers (thousands really) on this confusing subject and so, for me, drawing conclusions requires a lot of research. Luckily, most people interested in the climate debate already know the answer to the question of feedback from water vapor, so this article won’t be so interesting to them.

In fact, the paper under review doesn’t claim any real answers in the subject of water vapor feedback with climate change:

We are looking at regional variations in lapse rate in a fixed climate, rather than variations in the average lapse rate as the climate changes. This result demonstrates the unsuitability of using variations in different regions in our present climate as a proxy for climate change.

But even with the guarded comments of a published paper, the results are very interesting – and help, at the very least, to illuminate some aspects of how water vapor and atmospheric temperature interact to change the radiative cooling from the planet.

So for people looking for a quick answer, it’s not here. For people wanting to understand the interaction between surface temperature, atmospheric temperature, water vapor and outgoing longwave radiation (OLR) – this might provide a few insights on their journey.

Background

In trying to understand feedback we want to know what happens to the outgoing longwave radiation (OLR) from the climate as surface temperature changes.

Some basic (but hard to calculate) radiative physics – already covered in many places including CO2 – An Insignificant Trace Gas? Part Seven – The Boring Numbers (and the preceding parts of the series) – tells us that, all other things being equal, a doubling of CO2 in the atmosphere from pre-industrial levels will lead to a surface temperature change of about 1°C.

Apart from other variability – how will the climate respond to this increase in surface temperature?

It is only by isolating different causes and effects that we can hope to understand the complexity of the climate. It’s slow but there is more chance of getting the correct answer.

The main miscreant identified as possibly causing a much higher than 1°C increase is water vapor feedback. Water vapor is the dominant “greenhouse” gas, but is variable in space and time as it responds to climate conditions. See, for example, Clouds and Water Vapor – Part Two.

When we think about feedback, one of the most important considerations is how OLR responds to a change in surface temperature.

Let’s consider the change in surface radiation when the temperature increases by 1°C. Most of the earth’s surface has an emissivity very close to 1. At 15°C the increase in surface radiation for this 1°C increase, ΔR = 5.5 W/m². So if the OLR also increased by 5.5 W/m² then the feedback from the climate would be zero. (See comment below for why this is not quite correct).

Why? Because all of the increase in surface radiation has also been emitted from the climate system into space. Picture the scene if instead 10 W/m² was emitted into space after this 1°C increase in surface temperature – this would be negative feedback.

And if the OLR change was 1 W/m² ? This would be positive feedback. Because the increase in radiation from the surface wasn’t matched by radiation from the climate system.

If this doesn’t make sense, ask a question. It’s hard to make progress without grasping this point.

Measurements and “Model”

Dessler compares the results of over 100,000 measurements of top of atmosphere (TOA) fluxes from the CERES satellite with two band models which provide computational efficiency (see note 1).

Figure 1 – Comparison of a band model with measured results

This is simply to demonstrate that the model for calculating TOA fluxes is reliable and accurate. The results are used for later calculations. Other graphs in the paper compare the results against surface temperature and latitude to confirm that no bias exists in the results.

Atmospheric temperature and water vapor are measured using AIRS – Atmospheric Infrared Sounder flying on the NASA Aqua satellite. CERES= “Clouds and the Earth Radiant Energy System”, which is also flying on the Aqua satellite.

The measurements taken by AIRS and CERES are “virtually simultaneous”.

These measurements were all taken in March 2005 between 70°N and 70°S over the ocean under clear skies.

The measurements were selected from nighttime measurements. Why? To eliminate any contribution around the 4μm wavelength from solar radiation.

A Basic Equation

Equations aren’t fun for a lot of people and that’s understandable. Stay with me, I will try and explain it in plain English.

What we want to know is how OLR (radiation from the climate to space) changes as surface temperature changes. If we can establish this, we can understand how the climate currently responds to surface temperatures – and what feedbacks are currently in place, at least for the time under consideration:

Figure 2 – The equation

The red term is the main value we want to know – the “rate of change” of OLR with surface temperature

Or, how much does the outgoing longwave radiation change as surface temperature changes?

The orange term = the sum (vertically through the atmosphere) of all the changes in OLR as surface temperature changes, due to the change in atmospheric temperature

The green term = the sum (vertically through the atmosphere) of all the changes in OLR as surface temperature changes, due to the change in water vapor

And before we “dive in”, the basic concepts are, in simple terms:

if the atmosphere gets warmer it radiates more to space – and this cools the climate

if water vapor increases it reduces the OLR (because it is a “greenhouse” gas) – and this heats the climate (because less radiation to space takes place)

if water vapor increases it reduces the “lapse rate” (note 2), making the atmosphere warmer higher up, increasing radiation to space – and this cools the climate

Now let’s take a look at the graphical picture of how atmospheric temperature and humidity vary with surface temperature and height. Think of surface temperature as a proxy for latitude.

Here is how the air temperature vs height, and humidity vs height, vary with surface temperature:

from Dessler (2008)

Figure 3 – Measurements

For those new to humidity measurements in the atmosphere, note the strong dependency on surface temperature and on height in the atmosphere (1000hPa is the surface and 200hPa is around 12km above the surface).

Now we want to plot two of the terms in the equation (figure 2). The colors are matched up with the highlighted terms in the original equation.

From Dessler (2008)

Figure 4 – Calculated – Color text added

These values are calculated by using the model. (We have already seen that this band model accurately calculates the OLR from surface temperature, air temperature and humidity).

As you would expect, when air temperature increases by 1K the OLR increases – because a hotter atmosphere radiates at a higher intensity. This is with all other conditions held the same.

And as you might expect, when the humidity is increased by 10% the OLR decreases – because a more opaque atmosphere has a lower transmittance to surface radiation. This is with all other conditions held the same.

We have been calculating these terms from figure 2:

Now, find how OLR changes due to surface temperature changes we need to also find out these terms:

Or, in English:

the change in air temperature due to surface temperature changes

the change in humidity due to surface temperature changes.

From Dessler (2008)

Figure 5 – Measured – Color text added

So, to give an example of what these graphs show, we can see that at around 293-294K, an increase in surface temperature has little or no effect on humidity. Around 300K an increase in surface temperature has a large effect on humidity.

Now we are going to multiply the terms together to find:

the change in OLR with surface temperature – due to atmospheric temperature changes

the change in OLR with surface temperature – due to humidity changes

Figure 6 – Results – Color text added

The advantage of this method is that when we look at the summary and say, for example:

– we can review the terms that created the result and see which dominates – and why.

Looking at the total, we can see that between 298 – 303 K the OLR decreases as surface temperature increases (note that the plot is of the change in OLR as Ts increases versus Ts). And below 298 K the OLR increases as surface temperature increases.

This is in agreement with Raval & Ramanathan’s work based on ERBE data shown in Part One where the positive feedback comes from the tropics, and is reduced by the negative feedback from the sub-tropics and mid-latitudes.

The decrease of OLR as surface temperature increases became known as the super-greenhouse effect. Remember that any effect below an increase of 5.5W/m².K (at 15°C) is a positive feedback. (And at 30°C, this threshold value is 6.3W/m².K). An actual decrease of OLR as surface temperature increases is, therefore, a very strong positive feedback effect.

We can see the result plotted against surface temperature and height – now let’s see the total value against surface temperature, and some comparisons of the actuals vs reference scenarios:

Figure 7 – Color text and highlighting added

The first graph shows the change in OLR with surface temperature – due to atmospheric temperature changes. The blue line shows the result if the lapse rate was fixed. Remember that a lower value of changing OLR with Ts is more towards positive feedback.

This is a quantitative estimate of the effect of the changing lapse rate on dOLR/dTs, and it shows that it is negative for almost all values of Ts. In other words, as Ts increases, so does the lapse rate, and the general effect of this is to reduce dOLR/dTs, and therefore OLR, below what they would be if the atmosphere maintained a constant lapse rate.

The second graph shows the change in OLR with surface temperature – due to humidity changes. The purple line shows the result if relative humidity was constant. (And see the results from Sun & Oort, shown in Part Three).

In the subtropics, the ‘‘changing RH’’ line is positive, meaning that RH decreases with increasing Ts. This relative dryness contributes to high values of OLR here, providing a key pathway for the climate system to lose energy back to space. As Ts crosses the convective threshold, ≈298 K, the RH of the atmosphere abruptly increases, leading to a strong increase in q and a reduction in OLR and its gradient.

The third graph compares the results by using the data graphed in Figure 1 with the results derived through this article – and they are the same.

We also plot in this panel the right-hand side of equation (1):

Σi(∂OLR/∂Ti)(∂Ti/∂Ts) + Σi(∂OLR/∂qi)(∂qi/∂Ts) + ∂OLR/∂Ts,

derived from lines plotted in Figures 8a and 8b. As one can clearly see, the agreement is excellent. Note that this is a stringent test as these two lines are derived from completely independent data: one line is derived entirely from CERES data while the other line is derived entirely from AIRS data and a radiative transfer model. The excellent agreement gives us great confidence that, given observations of Ta and q, the clear-sky OLR budget is well understood inthe present atmosphere. We also see no evidence that neglected terms are important, in agreement with previous work..

Conclusion

The paper gives us an excellent insight into how atmospheric temperature and humidity vary as surface temperature varies – over the ocean. And how this maps into changes in OLR as surface temperature changes.

We see that the results are similar to Ramanathan’s work shown in Part One.

These are valuable insights.

If surface temperature increases from any cause, does this mean that positive feedback from water vapor will amplify this? If surface temperature reduces from any cause, does this mean that positive feedback from water vapor will amplify this?

Surely that depends.

But ask yourself this – if the results had shown the opposite effect, would you find them significant?

Articles in this Series

Part One – introducing some ideas from Ramanathan from ERBE 1985 – 1989 results

Part Six – Nonlinearity and Dry Atmospheres – demonstrating that different distributions of water vapor yet with the same mean can result in different radiation to space, and how this is important for drier regions like the sub-tropics

The HITRANS database contains 2.7M spectral lines and so “doing it the long way” takes a lot of time. Therefore, over time, many band models have been created – and critically evaluated – against the hard way.

Note 2: The lapse rate is the decrease in temperature as you go up through the atmosphere. In a dry atmosphere the temperature reduces at around 10K/km. In a very moist atmosphere the temperature reduces at around 4K/km. And, on average, the lapse rate is 6.5K/km. So the more water vapor there is in the atmosphere, the warmer the atmosphere at any given height.

SOD: This is a rather confusing paper and post. According to your post, you want to know: “In trying to understand feedback we want to know what happens to the outgoing longwave radiation (OLR) from the climate as surface temperature changes.” This paper seems only tangentially relevant to this subject.

You might change the first sentence of your conclusion to: “The paper gives us an excellent insight into how atmospheric temperature and humidity vary as surface temperature varies – over the ocean, AT NIGHT, WHERE THERE ARE NO CLOUDS. What are the implications of these limitations? This isn’t a global analysis.

According to the paper, “[20] As a starting point for our analysis, we expand dOLR/dTs, the derivative of OLR with respect to our SPATIAL coordinate Ts, in terms of Ta, q, and Ts”. “[54] … We reiterate that one should think of Ts as a
proxy for latitude, and not as a proxy for climate change.” They aren’t discussing feedback – the response of OLR to changing temperature – they are discussing the change with respect to LOCATION (which happens to have a different temperature) – and only those locations that are subsiding (clear) and only at night when the surface temperature is falling. In temperate zones, the physical location associated with a particular temperature moves dramatically north and south with the seasons. (In the Ramanathan study, temperature change was produced by the changing seasons – time – not changing location.)

What effect does the horizontal poleward convection of heat have on this analysis?

The paper doesn’t really appear to be about feedback at all. The authors simply show that observed OLR agrees with OLR calculated from Ts, Ta and water vapor using the same equations in your models. The rest of the paper is a geography lesson showing how Ts, Ta and water vapor (and therefore OLR) vary on PART of the planet. There is no response with time, everything is measured at the same time.

Dressler certainly could have been more candid about the limitations and implications of this study.

SOD: I’d start with what we know from “direct” measurements of water vapor and the change water vapor in the upper atmosphere. I believe AR4 cited a Soden Science? 2005? paper as the best evidence concerning this subject. Thanks for spending some time on feedbacks rather than easily-destroyed strawmen.

I was intrigued by the question you asked at the end of this post: “But ask yourself this – if the results had shown the opposite effect, would you find them significant?” Unfortunately, that is a question for advocates who believe one thing or the other. For scientists and engineers, a better question would be: “Do the methods and data in this paper provide meaningful information about water vapor feedback after a 1 degK temperature rise due to radiative forcing from 2X CO2?” The amount of feedback and one’s personal expectations about feedback based on other evidence (or prejudice) should be totally irrelevant.

Dressler shows us that as we change location from where it is 273 degK to 304 degK there is more water vapor in the atmosphere and this additional water vapor associated with these geographic and seasonal changes blocks some of the increase in OLR that would be predicted for higher temperature without additional water vapor. Speaking qualitatively, Dressler’s observations are a no-brainer – the humidity of the boundary layer over the ocean is in equilibrium with SST. Massive changes in SST must produce massive changes in the water content in the boundary layer above the ocean. However, the roughly 2 W/m2/degK of water vapor feedback (roughly 1 degK in isolation) predicted by the IPCC’s models for a 1 degK temperature rise before feedbacks depends on raising the water content of more than the boundary layer. In AR4, section 3.4.2.2 and Box 8.1 discuss the relative importance of water vapor in the mid- to upper troposphere compared with the boundary layer. Dressler’s approach doesn’t tell us anything about how water vapor changes with altitude. The real complexity of the problem can be seen in Figure 6 of publicly available Held and Soden (2000). In the section called the Satellite Era, H&S also explain some limitations of the type of studies done by R&R and Dressler.

However, the roughly 2 W/m2/degK of water vapor feedback.. depends on raising the water content of more than the boundary layer.

..Dressler’s approach doesn’t tell us anything about how water vapor changes with altitude.

The appeal of the paper to me is that does tell us about the water vapor change with altitude – every graph up until the end is plotted against pressure – so I’m confused by your statements.

It also tells us about the change in water vapor dominated by the regions with subsiding air (for newcomers – the areas with clouds are experiencing convection and AIRS can’t measure the water vapor below these).

Subsiding regions dominate – in terms of surface area – e.g. this graphic from Held and Soden 2000 in Part Three:

And it is the relationship between surface temperatures and water vapor in these areas which has most been questioned.

Dressler shows us that as we change location from where it is 273 degK to 304 degK there is more water vapor in the atmosphere and this additional water vapor associated with these geographic and seasonal changes blocks some of the increase in OLR that would be predicted for higher temperature without additional water vapor. Speaking qualitatively, Dressler’s observations are a no-brainer – the humidity of the boundary layer over the ocean is in equilibrium with SST.

(By the way, his name is Dessler).

The “no-brainer” analysis is Figure 3 (my numbering) = his Figure 4. And possibly the calculated OLR changes for each point on these graphs – although these two graphs have some interesting features which I’m sure aren’t that obvious to most readers.

But what is interesting is deriving the change in Ta and q as Ts changes – against altitude and against Ts.

As you correctly point out, this isn’t directly a change with time. However, given that sea surface will have changed during this month it isn’t a static result either.

One of the valuable insights these results give us is one which you yourself have requested previously – as surface temperature changes how does the lapse rate contribute to positive or negative feedback.

Here we see the comparison between the contribution of atmospheric temperature and humidity to changes in OLR. We see that the lapse rate provides negative feedback, while humidity provides positive feedback. And we can see how these relate to surface temperature.

SOD: I must confuse to not deeply understanding everything in Dessler’s paper. When I wrote before, it was after studying the Summary at the end of the paper, rather than the data you focused on in the above post.

I’m uncomfortable with the conclusion that the lower tropics is the region where increasing water vapor is likely to produce the greatest water vapor feedback. This conclusion may be an artifact of choosing an increase of 10% for q. One would get a very different answer if the chosen increase in q was the increase that brought q 10% closer to saturation (rather than 10% further from 0%). Dessler’s paper changes 80% relative humidity into 88% (absurd) and 30% into 33%. My suggestion would increase 80% to 82% and 30% to 37%. This seems more realistic to me. Absorbance changes with the log of the change in mixing ratio, so changes in less humid regions have greater potential to change absorbance. (As you have taught us, the wavelengths with about 50% transmittance have the greatest potential to increase radiative forcing, so increasing absorbance is only part of the story.)

Furthermore, the regions where humidity is high are the regions where convection and clouds can easily compensate for increased feedback from water vapor at low and middle altitudes. Some wild speculation: In zones where deep convection is common, the surface temperature could be controlled by the temperature at 100 mb and the lapse rate from there to the surface. If the temp at 100 mb doesn’t warm, the surface might not warm. Water vapor between the surface and 100 mb could be irrelevant because more water vapor produces increased convection, more clouds and more rain.

As noted by Dessler himself, changes in Ts in this paper are driven by changes in geography, not factors related to climate change. As one moves from one location to another, the humidity and circulation of the air overhead can change dramatically. See Soden & Held 2000 Figure 6 mentioned before. Small changes in Ts can represent moves under and out from under a massive region of dry subsiding air. Figure 6 is worth showing your readers. Dessler’s analysis gives me only hints of this circulation.

Soden and Held (2000) p450 suggests that the super-greenhouse effect may be an artifact of changes in circulation. They also say that the change in Gclear with Ts depends on what causes the change in Ts: a) the annual cycle (which changes the location of the ITCZ), year to year changes (via ENSO), or geographic changes.

Finally, I assume that increased water vapor feedback in the upper tropical troposphere is a major contributor to the infamous “hotspot”.

(I could use a refresher on feedback and how (W/m2)/degK or degK/(W/m2) works, summing in the infinite series to get temperature change, the non-linear aspects.)

This is certainly a good read, and ties directly into important questions related to tropical stability that is germane to anthropogenic climate change and paleoclimate. Though, it is worth emphasizing that the theoretical concepts described in this post are not new to the Dessler paper. While Dessler warns of its own limitations to climate change analyses, there’s still a good deal of utility in understanding feedbacks conceptually in these terms

1) The water vapor feedbacks acts to linearize the slope of the OLR vs. T curve, making it more linear than T^4. Climate sensitivity is inversely related to the steepness over which infrared cooling to space increases with the surface temperature, so flattening the curve makes sensitivity increase in the warm limit.

2) This topic and the comment by ClimateWatcher are relevant to the radiator fin hypothesis developed by Pierrehumbert (1995), in which a prime determinant of the tropical temperature stems from the efficiency through which the troposphere can radiate its heat to space. This is dependent on the extent and dryness of the
subsidence regions in the tropics, which is largely created by the large-scale circulation. In the subsiding regions the greenhouse effect from clouds and water vapor is weaker than in the convective regions, and therefore the emission of longwave energy is greatest.

3) In the high opacity limit, on a planet where the amount of greenhouse gas is temperature dependent, there are conditions (as first derived by Komabayashi 1967 and Ingersoll, 1969) (and separated as stratospheric and tropospheric limits by Nakajima, 1992) in which the OLR is independent of surface temperature completely, and if the solar radiation exceeds this limit than the result is a runaway greenhouse.

4) As many of the Held and Soden studies have noted, the water vapor feedback is dominated by the upper tropospheric layers,vwhere temperatures are significantly colder than the surface and can impact the OLR, and where the non-linear dependence between the radiative effect from water means that the even small changes in the humidity in drier layers can have the same impact as huge absolute increases in humidity that might be characteristic of the boundary layer.

2) It is worthy to note that the Beer-Lambert rule, valid locally for each vertical air column, might be overwritten on global scale; that is, formally, even larger total integrated q with the same global average Ts might lead to increased OLR, by redistributing spatially the Ts, Ta and q fields, if any physical constraint would require so.

3) Whether the real global atmospheric absorption acts in the direction chriscolose described above or into the opposite, that is, whether we face a runaway nightmare or our greenhouse effect is somehow physically stabilized, one has to calculate not only OLR, but also its contributing parts: surface transmitted and atmospheric upward emitted, separately. The two authors of the AIRS-CERES conversion did it, have found interesting relationships (considering DLR as well), and published their findings together in 2004 here: http://met.hu/idojaras/IDOJARAS_vol108_No4_01.pdf.

This conclusion may be an artifact of choosing an increase of 10% for q. One would get a very different answer if the chosen increase in q was the increase that brought q 10% closer to saturation (rather than 10% further from 0%). Dessler’s paper changes 80% relative humidity into 88% (absurd) and 30% into 33%. My suggestion would increase 80% to 82% and 30% to 37%. This seems more realistic to me.

The choice by Dessler isn’t absurd. Everyone (?) writing papers on water vapor discusses their choice for this calculation and no approach is without problems. See note at end as an illustration.

In any case, the important point to understand is that the choice doesn’t affect the result – unless there is a significant non-linearity.. let me explain.

Review this term:

Σi(∂OLR/∂qi)(∂qi/∂Ts)

The result does not depend on whether you choose a 1% change or 10% in RH or a 1% or 10% change in absolute humidity.

The result depends on upon the slope of the calculated term multiplied by the measured change in qi with Ts.

So perhaps we could say we would like to see a sensitivity analysis for the result in case the slope is substantially different for a small change vs a large change.

Does that make sense?

Note:

For example, in How Dry is the Tropical Free Troposphere? Implications for Global Warming Theory, Spencer & Braswell (1997), argue that additive changes in RH are the most appropriate for illustration:

To illustrate the latter point first, we have calculated the sensitivity of OLRCLR to additive changes of 3% RH..

Taking the extreme example of a totally dry troposphere, their method would indicate that a 3% increase in humidity would have no impact on OLRCLR (because 1.03 x 0 = 0).
Similarly, a 3% magnification of very small humidity values would also produce very weak impacts on OLR. As we will show, OLRCLR is actually the most sensitive to humidity fluctuations at the lowest humidities.

In any case, the comparison they make with Shine & Shina’s paper has no substantive difference, only an illustrative one.

In assessing this relative importance, one approach has been to assume equal fractional perturbations in mixing ratio (or, equivalently, vapor pressure), as in Shine & Sinha (6)..

Alternatively, Spencer & Braswell (49) perturb the relative humidities in different regions by equal amounts.. which weights dry regions more strongly, thereby emphasizing the free troposphere at the expense of the boundary layer and the subtropics over the tropics, as compared with Shine & Sinha..

There is no ambiguity as to how to compute the relative importance of different regions for water vapor feedback in a model that predicts changes in water vapor concentrations; the confusion only arises from differing presumptions as to a plausible model-independent starting point.

As noted by Dessler himself, changes in Ts in this paper are driven by changes in geography, not factors related to climate change. As one moves from one location to another, the humidity and circulation of the air overhead can change dramatically. See Soden & Held 2000 Figure 6 mentioned before. Small changes in Ts can represent moves under and out from under a massive region of dry subsiding air. Figure 6 is worth showing your readers. Dessler’s analysis gives me only hints of this circulation.

Fig 6 from Isaac Held & Brian Soden (2000) is very similar to the picture shown in Part Two:

No surprise because it is the same Brian Soden who wrote Chapter 10 of Frontiers of Climate Modeling.

I will give some thought to the “super-greenhouse” effect question – as to whether the results from Dessler rule out the “artifact” question raised by Held & Soden (2000) – and comment later.

The zonal averages of the total normalized atmospheric upward emittances are almost independent of the water vapor column amount

very interesting.

I have a sense of this from staring at water vapor satellite images.

The greatest emissions to space, in the H2O bands, seem to come from the subsident zones which also have very high water vapor content but capped closer to the surface.

One of the best nuggets I picked up from sod is that the emissive power of the GHGs depends on how the temperature of the atmosphere varies with height -and- how the constituent varies with height. CO2 is well mixed to 100km but H2O decreases rapidly moving up from the surface. The greatest vertical gradient in H2O occurs at the subsidence inversion.

Now consider that subsidence occurs -because- air aloft cools to somewhat counter the warming of subsidence – otherwise bouyancy would oppose the motion of subsidence.

Now further consider that the cooling which enables subsidence is because such air contains a longwave emitter, namely H2O.

So the presence of water vapor in the upper troposphere leads to subsidence which lowers the ‘top of the water vapor’, raising the H2O emissive temperature and increasing the emission to space for H2O.

Thus it appears there is negative feedback to water vapor radiative forcing.

SOD: In Figure 7, the strongest region of potential radiative forcing ((∂OLR/∂qi)(∂qi/∂Ts) = -0.5) due to increases in water vapor is centered at about 301 degK and 500 mb. Why does this region exist? When we are on the edge of either the upward or downward branches of the Hadley cell, there is a huge change in water vapor overhead associated with the geographic move that change surface temperature by 1 degK. As you move between regions of subsistence and convection, a small change Ts can be associated with big changes in q overhead, but the changes in q are not caused by Ts – they are caused by changes in circulation. So this dq/dTs isn’t classical feedback – which is the change in water vapor directly caused by warmer temperature. Dessler himself warns the reader changes in Ts are a proxy for changes in location and therefore could be different from changes induced by GHGs. So given a choice between Dessler’s analysis and any other one based on temperature change in a fixed location (ie R&R), I’d prefer the latter. Once you’ve digested S&H (2000) on the satellite era, if you say I’m still way off the mark, I’ll defer to your opinion (based on previous experience and my lack of comfort with the analysis in this paper).

The importance of Figure 5b depends on whether the chosen change in q (10% increase everywhere) makes sense. I agree with you that different scientists have made different choices for this change. Dessler doesn’t defend his choice; he simply cites the discussion in Soden&Held (2000), who actually made a very different choice (Equation 21) with radically different results – as can be seen in Figure 9 (at the end of their paper). If you were interested, a post comparing different approaches would be worthwhile. (That appears to be a hard job.)

For what it is worth, Soden&Held seem to be more open about discussing: a) how choices like this one influence results, b) explanations for the super-greenhouse effect, c) how different analyses give conflicting results, and d) the now-missing? “hot spot”. Perhaps this candor arises because theirs is a review article. Dessler could have been more candid. I wish S&H paper were more recent; perhaps a newer review would reach different conclusions. AR4 seems to think the upper atmosphere is most critical for water-vapor feedback, which is not surprising since Soden was an author of that section.

SOD: I agree that the ∂OLR/∂qi term is fixed by the physics. My problem is with the ∂qi/∂Ts term. In Dessler, the change is Ts is produced by moving to a location with a different Ts and looking to see how much water vapor (q) is now overhead. If I understand S&H (2000), if you stay at the same location and wait for the temperature to change seasonally, you will get a different answer (usually in terms of dOLR/dTs, not the individual components reported in this paper). If you wait for the temperature to change from year to year (mostly with ENSO), you will get a third answer. Even when you stay in one place, some regions that fluctuate between convection and subsistence the observed change is not directly related to the “water-vapor feedback” that will occur from rising GHG’s.

A simulation of the earth’s clear-sky long-wave radiation budget is used to examine the dependence of clear-sky outgoing long-wave radiation (OLR) on surface temperature and relative humidity. the simulation uses the European Centre for Medium-Range Weather Forecasts global reanalysed fields to calculate clear-sky OLR over the period from January 1979 to December 1993, thus allowing the seasonal and interannual time-scales to be resolved. the clear-sky OLR is shown to be primarily dependent on temperature changes at high latitudes and on changes in relative humidity at lower latitudes. Regions exhibiting a ‘super-greenhouse’ effect are identified and are explained by considering the changes in the convective regime associated with the Hadley circulation over the seasonal cycle, and with the Walker circulation over the interannual time-scale. the sensitivity of clear-sky OLR to changes in relative humidity diminishes with increasing relative humidity. This is explained by the increasing saturation of the water-vapour absorption bands with increased moisture. By allowing the relative humidity to vary in specified vertical slabs of the troposphere over an interannual time-scale it is shown that changes in humidity in the mid troposphere (400 to 700 hPa) are of most importance in explaining clear-sky OLR variations. Relative humidity variations do not appear to affect the positive thermodynamic water-vapour feedback significantly in response to surface temperature changes.

Abstract: This study presents a comparison of the water vapor and clear-sky greenhouse effect dependence on sea surface temperature for climate variations of different types. Firstly, coincident satellite observations and meteorological analyses are used to examine seasonal and interannual variations and to evaluate the performance of a general circulation model. Then, this model is used to compare the results inferred from the analysis of observed climate variability with those derived from global climate warming experiments. One part of the coupling between the surface temperature, the water vapor and the clear-sky greenhouse effect is explained by the dependence of the saturation water vapor pressure on the atmospheric temperature. However, the analysis of observed and simulated fields shows that the coupling is very different according to the type of region under consideration and the type of climate forcing that is applied to the Earth-atmosphere system. This difference, due to the variability of the vertical structure of the atmosphere, is analyzed in detail by considering the temperature lapse rate and the vertical profile of relative humidity. Our results suggest that extrapolating the feedbacks inferred from seasonal and short-term interannual climate variability to longer-term climate changes requires great caution. It is argued that our confidence in climate models’ predictions would be increased significantly if the basic physical processes that govern the variability of the vertical structure of the atmosphere, and its relation to the large-scale circulation, were better understood and simulated. For this purpose, combined observational and numerical studies focusing on physical processes are needed.

1) Is the term humidity directly interchangable with water vapour in this article? I think some of my following questions might be in error if I’ve wrongly assumed they are.

2) Why March 2005? Is there any sense that if you did the work on Feb2008 or June1998 you would get roughly the same result? Why couldn’t the work be done on the full sensor records? In light of that should your conclusion read

“The paper gives us an excellent insight into how atmospheric temperature and humidity vary as surface temperature varies – over the ocean, in March 2005.” (sorry for the pedantry, at least mine is different to Frank’s)

3) You wrote
“So, to give an example of what these graphs show, we can see that at around 293-294K, an increase in surface temperature has little or no effect on humidity. Around 300K an increase in surface temperature has a large effect on humidity.”

Why is this the case? What’s so special about 300K that it gives an apparent greater water vapour feedback? Why is there not a simple, direct relationship of >temperature leads to >humidity? Has this got anything to do with the Clausius-Clapeyron equation?

A recent post on SkepticalScience summarized the relationship between temperature and water vapour thus

“The amount of water vapor in the atmosphere exists in direct relation to the temperature. If you increase the temperature, more water evaporates and becomes vapor, and vice versa.”

4) This question maybe outside the scope of the discussion here but what are the implications for this work on climate sensitivity (CS) studies? I’m curious about work that has tried to estimate CS by looking at historical extreme periods such as the Last Glacial Maximum. If we took the LGM as an example global temp was 3-9oC lower, that would shift the range of latitudinal temperatures to the lower end of the temperature range on these graphs and probably a large section of the earth (the much expanded polar regions) would be off the bottom end of the graph. Water vapour feedbacks would potentially be radically different in the LGM to present. Is the complex relationship between temperature and humidity fully realised in these CS studies.

2) According to Figure 2, they collected 100-10,000 data points for each temperature between 273 and 305 degK in March 2005. Perhaps that was enough. Since Dessler doesn’t appear to tell us why he picked March 2005 and he doesn’t say that the results are typical of other times, he has given us no reason to believe they are typical. In Part I on water vapor, SOD showed the first satellite evidence for a strong water vapor feedback – a beautiful fit between global OLR and Ts for 1988 (out of four years of satellite data). Since I’ve never seen this key analysis repeated for any other time period (especially as better satellites came online), I’m left with two hypotheses: a) I’m incompetent at searching for confirmatory evidence. b) The result isn’t typical of how the earth behaves.

3) In Dessler’s paper, a surface temperature change from 293 to 294 degK and 300 to 301 degK both involve looking at data from different places and times, presumably places closer to the equator. When the data involves new locations, you can be entering or leaving a region where drier descending air or moister convecting air dominates. (If you are unfamiliar with the Hadley cell, read about it in Wikipedia.) The acknowledged weakness of Dessler’s paper is that temperature change is caused by moving to other places with new air overhead, not by waiting for a given location to warm and the humidity of the air overhead to respond to that new warmth.

Whenever someone mentions the Clausius-Claperyon equation and climate change, lookout! SkepticalScience is trying to imply that the physics of the Clausius-Claperyon equation guarantees that there WILL be more water vapor after GHG’s cause a temperature rise. The C-C equation tells us the maximum amount of water vapor air CAN hold at EQUILIBRIUM at a given temperature (100% relative humidity), not how much it DOES hold (which is 0-100% relative humidity). SkepticalScience ignores the fact that most of the atmosphere (except the boundary layer over the ocean) has not recently experienced the opportunity to come into EQUILIBRIUM with liquid water at the air’s current temperature.

Current climate models, not the C-C equation, predict that the relative humidity of the atmosphere will remain roughly constant as temperature rises. We know that climate models don’t have the resolution to accurately model convection and what happens as moist air rises in the atmosphere. The altitude to which convecting air rises determines how cold it gets, what type of clouds form, how much rain falls from it, and how dry it will be high in the atmosphere and while it descends. These climate models predict that water vapor feedback should make temperatures in the upper tropical troposphere rise faster than anywhere else on the planet. Thirty years of satellite observations are inconsistent with this prediction (but there are still arguments about whether the inconsistency has been demonstrated with <5% statistical uncertainty). Lindzen also claims that the models don't accurately predict how fast observed tropical rainfall increases with surface temperature, thereby allowing more water vapor to remain in the model atmosphere. (Dessler's methodology only tells us about the amount of water vapor in clear skies, thus my pendantry on this subject.)

4) Sometimes scientists try to calculate the temperature change associated with a particular radiative forcing (the no-feedbacks climate sensitivity) and then figure out how much changes in water vapor, clouds and other feedbacks will amplify this change. This approach has the advantage that we have an excellent understanding about the physics of how greenhouse gases will change the radiative balance of the planet and require some warming. Dessler's work and this post are directed towards understanding how much the "no-feedbacks climate sensitivity is amplified by water vapor. When all feedbacks are included, we have determined the (overall) climate sensitivity. Although we can accurately measure feedbacks in climate models, we can't directly observe a single feedback on the planet itself because everything changes at once. Does changing Ts cause q to change or does q or clouds cause Ts to change? To avoid this problem, scientists try to use past climate to determine the overall climate sensitivity without assigning any particular fraction of the temperature difference to any particular feedback. This approach includes your "complex relationship between temperature and humidity" (and clouds) as part of a black-box into which one feeds a change in radiative forcing and out of which comes a temperature change. The problem with this approach is that there is uncertainty about the forcings and temperatures during the LGM.

I’m having a little struggle with your (1) myself. I understand that the different terms for humidity mean different things, but I’m still resolving if they are kept distinct from one another in all parts of this post.

For instance,
q means specific humidity
vapor pressure is partial pressure and the maximum relates to C-C.
relative humidity is the ratio of the existing vapor pressure to the maximum

The turbulent air near the surface establishes a near-equilibrium condition with the water. I think it is safe to say that more water vapor is carried aloft under warmer conditions.

Obviously, if the relative humidity is staying about the same while the temperature is rising, there is more water vapor in the air in terms of partial pressure. Also, I would argue that where there are clouds, there is every opportunity for the air to come to equilibrium with water. In fact, that is pretty much why clouds exist; the temperature has fallen below the point of equilibrium.

So, if the atmosphere is overall a little warmer, and water forms clouds and precipitates as it cools, thereby maintaining an equilibrium of sorts, it follows that the water vapor that remains is a little more than it would be if the air were a little cooler.

It appears to me that the question is more “How much of a positive feedback will water vapor create?” than “Will water vapor create a positive feedback?”.

I have another question prompted by a small section in the Dessler paper.

“[37] It may be surprising that q decreases with increasing
Ts for Ts > 304 K. This makes sense, however, if one realizes that values of Ts > 304 K are only possible in
convectively suppressed regions. The suppression is provide by descending air, which tends to both cap convection and dry out the free troposphere, leading to cloud-free conditions. The clear skies, in turn, permit solar heating of the surface and high values of Ts.”

It’s interesting because it acknowledges the fact the clouds (and therefore cloud-free skies) are controlled by dynamical as well as thermodynamical processes. My reading of this section, in short, is by screening for cloud-free skies they are also screening for a particular set of dynamical conditions that are biasing the results for the convective tropical region.
It may be plainly obious how dynamical processes affect cloud formation in this region but surely dynamical processes are affecting cloud formation in all regions of the global. Screen for cloud-free skies anywhere on the global and you are also going to bias for a particular set of dynamical conditions that have the potential to bias the result. I don’t see where Dessler has attempted to control for this.

I had a quick skim read of this review (below) when thinking about this. It points out that some of Ramanathan’s work on this may have inadvertently attributed some of these processes to thermodynamics when dynamical processes may have dominated (page 4).

The factor that I don’t see in your discussion is the initial change in Ts due to the change in humidity. The formation of the water vapor at the surface requires significant heat for vaporization and would result in a Ts that is lower than would be present if the humidity had not been increased. Deserts are hotter during the day because of the absence of a source of water to absorb some of the heat through vaporization. Is the water vapor’s absorption of that heat and the initial reduction of Ts in your equation somewhere?

According to IPCC figures, a doubling of CO2 is supposed to block 3.7 watts, ultimately increasing the surface flux by 3.7 watts. You stated that any surface wattage increase below 5.5 watts would be a negative feedback, but an increase of 3.7 watts would completely offset the increase in flux due to CO2.

As others have pointed out, what Dessler is measuring is changes in surface flux in limited dry areas due to increases in surface radiation over the whole world. You’ve also got to factor in areas where there is increased evaporation, albedo changes due to increased cloud cover in some areas and reduced cloud cover in others, and changes in lapse rate due to higher absolute humidity.

Alan: The figure of 5.5 W/m2/degK comes from analysis of feedbacks and the IPCC’s figure of 3.7 W/m2 comes from analysis of radiative forcing (at the tropopause). Notice that the units are different. One definition for the greenhouse effect (G) comes from the equation below:

OLR = eoTs^4 – G

Without any greenhouse effect, outgoing long wavelength radiation (OLR) would equal graybody radiation for the earth’s surface at temperature Ts and the greenhouse effect reduces OLR from roughly 390 W/m2 at the surface to about 240 W/m2 at the top of the atmosphere. If we differentiate with respect to temperature:

(I assume the 5.5 W/m2 figure comes from assuming the earth is a blackbody. Surface radiation, W = 390 W/m2 divided by 288 degK times 4 gives 5.42 W/m2/degK.) dOLR/dTs is the observed change in OLR from space with surface temperature change, which is sometimes measured for the “whole” planet (70N to 70S) or smaller areas of the planet. dG/dTs is the change in the greenhouse effect as the earth warms and includes all feedbacks operating quickly enough to be observed as Ts changes (clouds, water vapor, convection/lapse rate, but not melting of ice-caps and vegetation changes).

The only rapid feedbacks operating in clear skies are water vapor feedback and lapse rate feedback. If we restrict the analysis to clear skies (by including a “c” in the name of each term):

dGc/dTsc = 5.4 W/m2/degK – dOLRc/dTsc

dGc/dTsc, the combined water vapor/lapse rate feedback, theoretically can be determined by satellite observations of dOLR/dTs in clear areas. Unfortunately, the locations and fraction of the earth covered by clouds changes with time and Ts and it is sometimes difficult to detect thin clouds from space. Does partitioning the earth into cloudy and clear regions allow us to accurately measure combined water vapor/lapse rate feedback? Do we get the same result over differing periods of time and when Ts changes for different reasons (volcanos, ENSO)? What if Ts is changed by natural variation in humidity or clouds rather than humidity and clouds responding to changes in Ts?

According to IPCC figures, a doubling of CO2 is supposed to block 3.7 watts, ultimately increasing the surface flux by 3.7 watts. You stated that any surface wattage increase below 5.5 watts would be a negative feedback, but an increase of 3.7 watts would completely offset the increase in flux due to CO2.

These are two completely different concepts.

The radiative forcing of CO2 (3.7W/m2 for a doubling of CO2 from pre-industrial levels) is the reduction in outgoing radiation as a result of the increased opacity of the atmosphere – prior to feedbacks (see note).

The increase in OLR as surface temperature increases is a measure of positive or negative feedback (from any causes). The neutral case is where the increase in OLR balances the increase in the surface radiation. If OLR increases less than this it means that the climate is demonstrating positive feedback.

Two different parameters. The only thing they have in common is they are measured in the same units.

Note: the value of radiative forcing is measured after stratospheric equilibrium to the new atmospheric conditions but prior to any surface/tropospheric adjustment. The value of radiative forcing is also measured at the tropopause.

I think Frank has answered your questions pretty well. Your first question – yes humidity is the measure of the amount of water vapor so these terms are used inter-changeably.

And on March 24, 2011 at 2:50 am:

It’s interesting because it acknowledges the fact the clouds (and therefore cloud-free skies) are controlled by dynamical as well as thermodynamical processes. My reading of this section, in short, is by screening for cloud-free skies they are also screening for a particular set of dynamical conditions that are biasing the results for the convective tropical region.
It may be plainly obious how dynamical processes affect cloud formation in this region but surely dynamical processes are affecting cloud formation in all regions of the global. Screen for cloud-free skies anywhere on the global and you are also going to bias for a particular set of dynamical conditions that have the potential to bias the result. I don’t see where Dessler has attempted to control for this.

They are measuring only clear skies because there is no way to do these measurements under cloudy skies.

And you are right, there is no control for this.

But here is what I find interesting about it – the results are biased towards descending air, or at least, biased towards ignoring the convection which causes cloud formation.

If Dessler’s measurements somehow screened out descending air in favor of rising air there would be a clear bias towards measuring the “inevitable results of air circulation” (see below) and not climate feedback.

Measuring only descending air, or at least removing the measurements of air that generates clouds, gives us a bias in the other direction.

“The inevitable results of air circulation” describes the mechanism which Frank has already discussed, and which you can read about in Part Three – rising air has recently been in equilibrium with the ocean surface and so started with 100% relative humidity whereas descending air has recently been detrained of much of its water vapor and its absolute humidity has been determined by the coldest temperature reached on its journey.

So measuring rising air means that we see the results of the Clausius Clapyron relationship – which tells that that hotter temperatures lead to more water vapor.

They are measuring only clear skies because there is no way to do these measurements under cloudy skies

Let’s not forget this.

CO2 emission to space takes place well above the clouds ( in the stratosphere ).

H2O emission in the H2O bands takes place from the cloud tops, if they are present, or from the H2O if no clouds exist, and from significantly lower if subsidence is occurring.

When I look at where emissions to space occur in the water vapor bands the relationship (∂OLR/∂qi)(∂qi/∂Ts) does not appear to apply at all:

The much more humid Caribean Sea is emitting much more energy to space than is the much drier Nevadan desert or Hudson Bay.

In the water vapor bands, OLR is not strictly a function of q, but more a function of what the temperature of the emitting layer of water vapor is, governed mostly be vertical motion and clouds, which are part of the general circulation.

While the OLR change from CO2 is largely unaffected by circulation because that forcing takes place in the stratosphere, the effect of H2O may very well be constrained by the motion of the atmosphere and by the negative feedback that H2O emissions create to induce subsidence:

Notice the peak in subsidence due to radiative cooling (red) at about 11km. That cooling take place largely due to the ‘top’ of the water vapor. If water vapor is present, subsidence takes place due to cooling – sounds like negative feed back to me.

“Measuring only descending air, or at least removing the measurements of air that generates clouds, gives us a bias in the other direction.”

Is that the best way to look at it? In the final quote you use from Sun and Oort in part 3 they describe the situation thus

“the influence from the sea is restricted to a shallow boundary layer and the free tropospheric water vapor content and temperature are physically decoupled from the sea surface temperature underneath.”

Once you accept that you are specifically looking at descending air don’t you also have to accept that the properties of that air are not being generated by the SST below it? There seem to be very different assumptions underlying S&O’s “decoupled” situation with your ‘low biased’ description.

With what is reported in the paper it is entirely conceivable that the “tropical region” shows the high positive feedback due to a rising branch of the circulation, and the “sub-tropical region” with lower positive feedback due to a descending branch of the circulation.

Let’s take that as a working hypothesis for now.

Notice that even in this descending region, where the air has been detrained of moisture due to its recent journey through cold air, the term:

(∂OLR/∂qi)(∂qi/∂Ts)

is still well below the threshold for zero feedback (“well below” = positive feedback).

(I have stared at these various graphs for so long that I forgot what they meant – “0” is not zero feedback, it is positive feedback).

So demonstrating that in the month in question, at night, between 70’S to 70’N, the entire region demonstrates positive feedback from water vapor – whether in rising or descending branches of the circulation. And at every altitude.

We also get to see the comparison of the actual result – for this month – compared with what the result would be if relative humidity stayed constant (vs Ts). We see that the real atmosphere is not far off conserving relative humidity (as also reported by Sun & Oort 1995, shown in Part Three).

As to what happens when the climate changes, it is a different question.

What this paper helps us see is that the question about water vapor above the boundary layer is somewhat answered. (“Somewhat” because it is one month of data under clear skies).

The discussion in Part Three posed this question – which you have so well described in your answer to HR on March 25, 2011 at 9:03 pm.

I think that Dessler’s paper sheds some light on the answer.

Maybe I’m wrong. As I said at the start of the article, this is a very complex subject.

CO2 emission to space takes place well above the clouds ( in the stratosphere ).

What is your source for that claim?

I expect it is true for a very narrow part of the spectrum. See the transmittance graph for the troposphere in Understanding Atmospheric Radiation and the “Greenhouse” Effect – Part Nine for illustration of the varying transmittance of the atmosphere at different wavelengths due to CO2. As you can see there are regions where the transmittance of the whole troposphere is around 0.5 or more and even where the transmittance is 0.1 for the whole troposphere the cooling to space will come from within the troposphere.

(Eventually I will get around to completing the model to incorporate the Doppler broadening, via the Voight profile, and I will be able to calculate exactly where the average emission to space comes from as a function of wavelength).

The much more humid Caribean Sea is emitting much more energy to space than is the much drier Nevadan desert or Hudson Bay.

Can you explain what you are claiming? Generally the drier deserts emit much more radiation to space than the oceans at the same temperature. The dry air allows the surface radiation through mostly unabsorbed. Over the oceans the humidity means that surface radiation is absorbed and re-emitted at colder temperatures.

In the water vapor bands, OLR is not strictly a function of q, but more a function of what the temperature of the emitting layer of water vapor is, governed mostly be vertical motion and clouds, which are part of the general circulation.

OLR is never just a function of q or the concentration of radiatively-active gases (“greenhouse” gases) – it is a function of the temperature as well.

Everyone knows this and so this is why the equations used to calculate OLR match the measurements of OLR (at the start of the paper).

As you suggest, however, the wings of the CO2 band show up in channels 2 through 5, which originate in the troposphere.

——The much more humid Caribean Sea is emitting much more energy to space than is the much drier Nevadan desert or Hudson Bay.——

“Can you explain what you are claiming? Generally the drier deserts emit much more radiation to space than the oceans at the same temperature. The dry air allows the surface radiation through mostly unabsorbed. Over the oceans the humidity means that surface radiation is absorbed and re-emitted at colder temperatures.”

Yes that is what is claimed, but not observed, at least from the ‘Water Vapor’ satellite imagery:

I emailed Professor Dessler about a couple of these questions. I should have done that at the outset.

Here is his very interesting response (reproduced with his permission):

====

Hello and thanks for your interest in my research. The short answer to your question is that I do not think that this paper by itself tells us much about the water vapor feedback. As you pointed out, what you’re really seeing is the variation across different circulation regimes—e.g., rising and descending branches of the Walker/Hadley cells.

What I was trying to do in this paper is develop the analytical tools to decompose observed top-of-atmosphere fluxes into those parts caused by changes in water vapor, temperature, albedo, and clouds. However, at the very same time I was working on this, the problem was solved
(and better than I could’ve done it) by Brian Soden in his 2008 J. Climate paper. So I stopped working on it and just used his approach.

If you read his paper, you’ll see that we were definitely on the same track, but he was pretty far ahead of me.

Once I had the tools to break down top-of-atmosphere fluxes into the parts caused by water vapor, clouds, etc., I could then quantify the water vapor feedbacks, which I did in these papers:

I also used a similar approach in evaluating the cloud feedback (Dessler, A.E., A determination of the cloud feedback from climate variations over the past decade, Science, 330, doi:10.1126/science.1192546, 1523-1527, 2010).

At this point, I would say that the water vapor feedback is quite well understood. The idea of a strong and positive water vapor feedback is now supported by simple theory (e.g., Minschwaner, K., and A.E. Dessler, Water vapor feedback in the tropical upper troposphere: Model
results and observations, J. Climate, 17, 1272-1282, 2004; Dessler, A.E., and S.C. Sherwood, A matter of humidity, Science, 323, 1020-1021, DOI: 10.1126/science.1171264, 2009) as well as observations, and it is also well reproduced by climate models.

You can get reprints of all of these papers on my web site.

And yet, some skeptics still argue that the water vapor feedback is unproven/uncertain. This is a classic zombie argument. While it may have had validity 15 or 20 years ago, it no longer does. But no matter how many times it is refuted, it keeps coming back. As a scientist, I can’t tell you how frustrating that is.

As far as why I only used one month, it was as you supposed mainly because of the amount of data and the complexity of the calculation made doing many more months too difficult. And there was really no point—given that the techniques work on this one month, there’s no reason to think it wouldn’t work on any other month.

There are two 2008 papers in J Climate with links to the abstracts and then the full text. I suspect the paper with radiative kernels is the reference Dessler mentioned. At first glance, this paper is about analysis of model feedbacks, not observational data.

I had previously glanced at Dessler GRL 2008 and not found a rational for the time periods chosen for analysis.

The Brian Soden link above is the paper – it is also referenced from Dessler’s 2008 GRL paper.

I had not understood the importance of Soden’s paper and although I have previously taken a look at it, I had not taken the time to read it. Well, it’s not an easy read but I expect it is worthwhile. So that is some homework.

Dessler’s 2008 GRL paper does look good and I have read it previously, although on rereading it today I have some “rookie questions” – that will probably disappear when I reread it again in the next few days.

The theory paper – Minschwaner, K., and A.E. Dessler, Water vapor feedback in the tropical upper troposphere: Model results and observations, J. Climate – is not an easy read either, but does have some very interesting analysis. If I ever feel like I understand it I will try and write about it..

I agree with your comment about a lot of homework to do on water vapor feedback. When Lindzen debated North, he made a remark about new evidence strengthening the case for a significant water-vapor feedback. The hard part is identifying the key papers. If radiative kernels are the key, then Soden 2008 may be the place to start. The Soden 2010 paper I linked appears to apply this methodology to all of the ERBE data from the 1980’s (you may remember complaints that R&R showed data for only 1988) as other satellite data (CERES?) in the 2000’s.

I’m forced to agree with you that combined water vapor/lapse rate feedback from clear skies is telling us a lot about the behavior of subsiding regions of the atmosphere – the regions which have had the least opportunity to come into equilibrium with liquid water (warmed by radiative forcing from GHGs). The regions hidden by clouds are certainly more likely to have recently been in equilibrium with liquid water. Unfortunately, a region that is cloudy right now may be clear in a few hours and the amount of convection varies (stops? partly reverses?) with the daily insolation cycle. If there were a stable separation between cloudy convective regions and clear subsiding regions, interpretation of clear sky feedback would be more straightforward.

In the long run, – IF my understanding of the situation is correct – these observations concerning water vapor feedback in tropical clear skies need to be reconciled with other observations concerning the apparent absence of a “hotspot” in the upper tropical troposphere over the last 30 years. One set of data or the other may be wrong or misinterpreted or cloud feedback could be strongly negative.

The peak at 300K in Dessler’s fig6b (your figure 5) is still interesting me. It seems it could equally be explained in dynamical terms. Superficially some of the features of Desslers Fig 6b (and 7b maybe more so) seem to be describing the boundary regions of Hadley and mid-latitude cells. I’m assuming 280K is ~60 degrees latitude and 295 is ~30 degrees latitude. 300K maybe be the peak effect of dynamical processes of moving the warmest, most humid air into slightly cooler regions

What happens to the hot CO2 (432,000 kg) and OH2 (177,000 kg) that are released into the stratosphere at ca 35,000 ft? The air pressure at this height is ca 5 lbs per sq inch.

I asked Gavin about this and he didn’t know.

Since the tropopause is a barrier that retards mass exhange between the troposphere and stratosphere, how might these exhaust gases from the many thousands of dialy flights effect OLR? Would there be “extra” warming in the stratosphere?

If you watch a high flying jet, the contrails completely disappear after a short distance. Presumably, the initally condensed gases dissapate by evaporation.

Why don’t you run the numbers yourself? Take a cylinder the diameter of the plane’s wingspan and the length of the trip and calculate the change in CO2 and water vapor in that volume. The contrails themselves probably have more effect on the environment than the increase in CO2 and H2O.

Let’s consider the change in surface radiation when the temperature increases by 1°C. Most of the earth’s surface has an emissivity very close to 1. At 15°C the increase in surface radiation for this 1°C increase, ΔR = 5.5 W/m². So if the OLR also increased by 5.5 W/m² then the feedback from the climate would be zero.

This is a problem statement.

The principle is correct, but if the surface increases in temperature by 1’C, a zero feedback response of OLR is not 5.5 W/m².

The no feedback response is more like 3.3 W/m² and isn’t a one-line derivation. This is because a 1’C surface rise translates – with no feedback – into an increase of the atmospheric temperature which results in a change in outgoing radiation from the atmosphere, not from the surface.

“Some basic (but hard to calculate) radiative physics – already covered in many places including CO2 – An Insignificant Trace Gas? Part Seven – The Boring Numbers (and the preceding parts of the series) – tells us that, all other things being equal, a doubling of CO2 in the atmosphere from pre-industrial levels will lead to a surface temperature change of about 1°C.”

There is a much easier way to calculate the often quoted 1 C of “intrinsic” warming from 2xCO2. But the problem with this number is the surface forcing of 3.7 W/m^2 from 2xCO2 (assuming all of it will be incident on the surface) really only provides 0.7 C of ‘direct’ warming. The often quoted 1.1 C total comes from adding on net transmittance to space or about 0.6 for a total of 5.9 W/m^2 (3.7 x 0.6 = 2.2 W/m^2; 2.2 + 3.7 = 5.9 W/m^2;. +5.9 W/m^2 from S-B = +1.1 C).

This is misleading because the lion’s share of all the feedbacks (known and unknown) are already embodied in the net transmittance to space from decades (even centuries or millennia) of the surface’s response to solar forcing.

Also, if the claim is that +3.7 W/m^2 at the surface is going to become +16.6 W/m^2 (+3 C) mostly through ‘feedback’, you better be able to explain why it doesn’t take 1075 W/m^2 emitted at the surface to offset the 239 W/m^2 coming in from the Sun (16.6/3.7 = 4.5; 1075/239 = 4.5).

You also better be able to explain why the surface will respond to GHG ‘forcing’ nearly 3 times as powerfully as it does to solar forcing (390/240 = 1.6; 4.5/1.6 = 2.8).

That an extra 3.7 watts at the surface will respond nearly 3 times as powerfully as the original 98+% (239 W/m^2) from the Sun is an extraordinary claim that requires extraordinary proof.

In other words, you better be able to quantify specifically how and why the feedback will cause this much change on the next few watts and why it doesn’t on the original 98+%, and even further, you better be able to explain specifically where the additional 10.7 W/m^2 are coming from (16.6 – 5.9 = 10.7).

There is an even easier way to get the 1.1 C from 2xCO2. Just multiply the the 3.7 W/m^2 by the reciprocal of net transmittance to space, which is just the surface response to solar forcing (3.7 x 1.6 = 5.9 W/m^2) and convert to temperature via Stefan-Boltzman.

Also, there is much better and easier way to explain physically what is happening to cause 1.1 C rise from 2xCO2.

When there is a radiative imbalance, i.e. from additional CO2 added to the atmosphere which redirects more outgoing surface radiation back to the surface, there is reduction in the amount of LW radiation leaving at the top of the atmosphere (more radiation is arriving from the Sun than is leaving at the top of the atmosphere). To achieve equilibrium, the surface warms up until it again radiates the same amount of energy as is arriving from the Sun.

To give a numerical example, there is about 239 W/m^2 arriving post albedo from the Sun, 239 W/m^2 leaving at the top of the atmosphere, and the surface is emitting 390 W/m^2. This represents the system in equilibrium (energy in = energy out). In simple energy balance terms, this means that it takes 390 W/m^2 at the surface to allow 239 W/m^2 to leave the system, offsetting the 239 W/m^2 coming in from the Sun. If there was a radiative imbalance (or ‘radiative forcing’) of 3.7 W/m^2 from a doubling of CO2, the energy leaving at the top of the atmosphere would reduce by 3.7 W/m^2 to 235.3 W/m^2 (239 – 3.7 = 235.3). In this example, +3.7 W/m^2 is received by the surface for a new total of 393.7 W/m^2. If the +3.7 W/m^2 is treated the same as the 239 arriving from the Sun, it will be amplified by a factor of about 1.6 (390/239 = 1.6), as this represents the surface response to forcing of any kind. 3.7 W/m^2 x 1.6 = +5.9 W/m^2 to allow an additional 3.7 W/m^2 to leave the system to restore equilibrium (239 W/m^2 in and out). The new surface emitted radiation would be 395.9 W/m^2 (390 W/m^2 + 5.9 W/m^2), which corresponds to about a 1.1 C rise in temperature.